Turn Any Video into a Transcript with AI in Seconds

Ever found yourself scrubbing through a 45-minute conference talk just to find that one key point the speaker made? Or maybe you’ve needed a quick summary of a tutorial before deciding to watch the whole thing. Manually transcribing or summarizing video is a tedious chore. What if you could offload that entirely to a simple script?

That’s exactly what video-to-txt does. It’s a clean, open-source Python tool that automates the entire process: from video file to a clean transcript and a concise AI-generated summary, ready in moments.

What It Does

In short, video-to-txt is a command-line tool that takes a video file (like an MP4), extracts the audio, transcribes it using OpenAI's Whisper (a state-of-the-art speech recognition model), and then sends that transcript to an LLM (like GPT-4 or Claude) to generate a structured summary. You get two text files as output: a full transcript and a neatly formatted summary breaking down the key points.

Why It's Cool

The magic here is in the simplicity and the smart choice of underlying tech. Instead of being a hosted service with limits, it’s a script you run locally. It leverages Whisper, which is not only highly accurate but also runs offline, keeping your data private for the transcription step. The optional LLM summary step is configurable, so you can plug in your preferred model API.

Some standout features:

• Local First: The core transcription happens on your machine using Whisper. No uploading sensitive meeting recordings to unknown servers.
• Flexible AI Summary: It uses LiteLLM, meaning you can easily switch between OpenAI, Anthropic, Gemini, or other supported providers with a simple config change.
• Developer-Friendly: It’s a Python project with a clear README. The code is straightforward, making it easy to fork and modify—maybe to add translation, custom summary formats, or to integrate into a larger pipeline.
• Solves a Real Problem: For developers, this is perfect for digesting tech talks, documenting team stand-up recordings, creating notes from coding tutorials, or pre-processing content for a blog post.

How to Try It

Getting started is straightforward. You’ll need Python and ffmpeg installed on your system.

1. Clone the repo:

   git clone https://github.com/lza6/video-to-txt.git
   cd video-to-txt
   

2. Set up a virtual environment and install dependencies:

   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate
   pip install -r requirements.txt
   

3. Configure your API key (for the summary feature): Duplicate the .env.example file to .env and add your OpenAI (or other provider) API key.

4. Run it:

   python main.py --input /path/to/your/video.mp4
   

   That’s it. Check the outputs/ folder for your _transcript.txt and _summary.txt files.

For all the details and advanced options (like specifying the Whisper model or LLM), check out the GitHub repository.

Final Thoughts

As developers, we often consume and create video content. video-to-txt feels like a utility that should have existed all along—a sharp, focused tool that does one job exceptionally well. It removes the friction from getting text out of video, which is the first step to making that content searchable, indexable, and truly useful.

The project is a great example of gluing together powerful AI models into a practical workflow. It’s also a perfect starting point if you want to tinker, perhaps by adding a simple GUI, hooking it up to a Discord bot, or automating the processing of entire directories of videos.

Give it a spin next time you have a long video to process. It might just save you an hour.

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